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Deploying in a Docker Swarm

Docker Swarm can be used to quickly spin up a distributed Pravega cluster that can easily scale up and down. Unlike docker-compose, this is useful for more than just testing and development. In future, Docker Swarm will be suitable for production workloads.

Prerequisites

  • A working single or multi-node Docker Swarm. Please refer to swarm-tutorial.

  • HDFS and ZooKeeper. We provide compose files for both of these, but both are single instance deploys that should only be used for testing/development.

More information to deploy our HDFS and ZooKeeper can be found here. Please refer to hdfs.yml and zookeeper.yml files.

docker stack up --compose-file hdfs.yml pravega
docker stack up --compose-file zookeeper.yml pravega

This runs a single node HDFS container and single node ZooKeeper inside the pravega_default overlay network, and adds them to the pravegastack.

HDFS is reachable inside the swarm as

hdfs://hdfs:8020
ZooKeeper is reachable at

tcp://zookeeper:2181.

Either one or both of these can be initiated for running, but serious workloads cannot be handled.

Network Considerations

Each Pravega Segment Store needs to be directly reachable by clients. Docker Swarm runs all traffic coming into its overlay network through a load balancer, which makes it more or less impossible to reach a specific instance of a scaled service from outside the cluster. This means that Pravega clients must either run inside the swarm, or we must run each Segment Store as a unique service on a distinct port.

Both approaches are demonstrated in the below section.

Deploying (Swarm only clients)

The easiest way to deploy is to keep all traffic inside the swarm. This means your client apps must also run inside the swarm.

ZK_URL=zookeeper:2181 HDFS_URL=hdfs:8020 docker stack up --compose-file pravega.yml pravega

Note that ZK_URL and HDFS_URL don't include the protocol. They have default values assigned as zookeeper:2181 and hdfs:8020, when deployed using zookeeper.yml/hdfs.yml.

Your clients must then be deployed into the swarm, using the following command.

docker service create --name=myapp --network=pravega_default mycompany/myapp

The crucial bit being

--network=pravega_default.
Your client should talk to Pravega at

tcp://controller:9090`.

Deploying (External clients)

If you intend to run clients outside the swarm, you must provide two additional environment variables, PUBLISHED_ADDRESS and LISTENING_ADDRESS. PUBLISHED_ADDRESS must be an IP or Hostname that resolves to one or more swarm nodes (or a load balancer that sits in front of them). LISTENING_ADDRESS should always be 0, or 0.0.0.0.

PUBLISHED_ADDRESS=1.2.3.4 LISTENING_ADDRESS=0 ZK_URL=zookeeper:2181 HDFS_URL=hdfs:8020 docker stack up --compose-file pravega.yml pravega

As above, ZK_URL and HDFS_URL can be omitted if the services are at their default locations.

Your client should talk to Pravega at

tcp://${PUBLISHED_ADDRESS}:9090`.

Scaling BookKeeper

BookKeeper can be scaled up or down using the following command.

docker service scale pravega_bookkeeper=N

As configured in this package, Pravega requires at least 3 BookKeeper nodes, (i.e., N must be >= 3.)

Scaling Pravega Controller

Pravega Controller can be scaled up or down using the following command.

docker service scale pravega_controller=N

Scaling Pravega Segment Store (Swarm only clients)

If you app will run inside the swarm and you didn't run with PUBLISHED_ADDRESS, you can scale the Segment Store the usual way using the following command.

docker service scale pravega_segmentstore=N

Scaling Pravega Segment Store (External clients)

If you require access to Pravega from outside the swarm and have deployed with PUBLISHED_ADDRESS, each instance of the Segment Store must be deployed as a unique service. This is a cumbersome process, but we've provided a helper script to make it fairly painless:

./scale_segmentstore N

Tearing down

All services, (including HDFS and ZooKeeper if you've deployed our package) can be destroyed using the following command.

docker stack down pravega